This is a comprehensive two-day course designed for non-technical mid-level and senior managers aiming to deepen their understanding of Artificial Intelligence. This course covers fundamental AI concepts, explores the intricacies of Generative AI, and demonstrates practical ways AI can boost productivity within organizations. Through interactive sessions, case studies, and discussions on the latest AI technologies, participants will gain valuable insights into leveraging AI for strategic advantage.
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Led by industry experts, our HRDC Claimable training programs cover cutting-edge topics, equipping you with the skills needed to drive innovation and excel in the digital age.
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Data Storytelling
Data storytelling is a critical skill for conveying data-driven insights in a compelling and meaningful way. This three-day course, designed for beginners, focuses on teaching the art and science of data storytelling. Participants will learn how to structure, visualize, and present data to engage and inform their audience effectively.
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Big Data Hadoop
Hadoop is a foundational technology for processing and analyzing massive volumes of data. This three-day course, tailored for beginners, provides a comprehensive introduction to the core concepts of Big Data and Hadoop. Participants will gain an understanding of distributed storage and processing, Hadoop ecosystem components, and hands-on experience with Hadoop tools.
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Deep Learning and Natural Language Processing
Deep Learning and Natural Language Processing (NLP) have revolutionized the way we interact with and analyze text data. This four-day course, tailored for beginners, provides a comprehensive introduction to the foundations of deep learning and its application in NLP. Participants will gain a strong understanding of neural networks, language processing, and hands-on experience in building NLP models.
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Machine Learning – Unsupervised Learning
Unsupervised learning is a fascinating field of machine learning that discovers patterns, structures, and relationships within data without the need for labeled examples. This three-day course, designed for beginners, offers a comprehensive introduction to unsupervised learning techniques. Participants will gain a solid understanding of clustering, dimensionality reduction, and anomaly detection.
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Machine Learning – Classification and Forecasting
Machine learning is a powerful tool for classification and forecasting tasks, which are at the core of data-driven decision-making. This two day course, designed for beginners, provides a comprehensive introduction to classification and forecasting using machine learning algorithms. Participants will learn the fundamentals, practical application, and best practices in predictive modeling.
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Machine Learning – Regression
Machine Learning plays a pivotal role in predictive analytics, and regression is a fundamental technique within the field. This two-day course is designed for beginners and focuses on teaching the core concepts and practical application of regression algorithms. Participants will learn how to build, evaluate, and interpret regression models, making it an ideal starting point for a data science journey.
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Data Wrangling & Exploratory Data Analysis with Python
Data wrangling and exploratory data analysis (EDA) are essential steps in any data science or analysis project. This four-day course is designed for beginners and provides a comprehensive foundation in data preparation and exploration using Python. Participants will learn to clean, transform, and gain insights from real-world datasets, making them well-equipped for data-driven decision-making.
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SQL for Data Science
SQL (Structured Query Language) is the backbone of data retrieval and manipulation for data scientists. This two-day course is designed for beginners, providing essential skills for working with databases. Participants will learn to write SQL queries to extract, analyze, and manage data, a fundamental skill for anyone in the field of data science.
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Python for Data Science and Analytics
Python has become the go-to language for data science, and this three-day course is designed to introduce beginners to the world of data analysis, visualization, and machine learning using Python. Participants will gain hands-on experience with Python libraries and tools essential for data science, empowering them to embark on a data-driven journey.
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Supply chains are becoming increasingly complex, global, and data-intensive. Volatile demand, disruptions, sustainability requirements, rising logistics costs, and customer expectations are forcing organisations to move beyond traditional planning tools toward AI-enabled, adaptive supply chains.
Artificial Intelligence (AI), particularly Machine Learning, Large Language Models (LLMs), and Generative AI, is transforming how organisations forecast demand, manage inventory, optimise transportation, monitor suppliers, and respond to disruptions in real time. Today, supply chain professionals—not just data scientists—can directly use AI tools to analyse data, generate insights, summarise operational reports, support decision-making, and improve coordination across functions.
This course provides a practical, business-focused introduction to AI for supply chain professionals. Participants will learn AI fundamentals, understand how AI technologies interconnect, and gain hands-on experience with leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM. The emphasis is on real-world supply chain use cases, responsible AI usage, and measurable operational improvements, without requiring programming skills.
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System Analysts play a pivotal role in translating business requirements into technical system designs, ensuring alignment between users, processes, data, and technology. As systems become more complex and organisations demand faster, more adaptive solutions, Artificial Intelligence (AI) is emerging as a powerful capability to support modern systems analysis.
Advances in Machine Learning, Large Language Models (LLMs), and Generative AI enable system analysts to analyse requirements more efficiently, document system specifications, model processes, assess system impacts, and support solution design with greater speed and clarity. AI tools can assist across the full systems analysis lifecycle—from requirements elicitation and system modelling to documentation, validation, and change analysis.
This course provides a practical, system-focused introduction to AI for System Analysts. Participants will gain a clear understanding of AI concepts, explore how AI technologies interconnect, and gain hands-on experience using leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM. The emphasis is on real system analysis use cases, responsible AI usage, and improving the quality and consistency of system deliverables—without requiring programming skills.
